基于低功耗SoC的两栖球形机器人运动目标检测系统资源-CSDN文库

研究论文

132 浏览量 2021-03-06 08:18:07 上传评论收藏 1.22MB PDF 举报

资源推荐

资源详情

资源评论

A Low-power SoC-based Moving Target

Detection System for Amphibious Spherical Robots

Shaowu Pan

1, 2, 3

, Liwei Shi

1, 2, 3,*

, Shuxiang Guo

1, 2, 3, 4

, Ping Guo

1, 2, 3

, Yanlin He

1, 2, 3

and Rui Xiao

1, 2, 3

The Institute of Advanced Biomedical Engineering System, School of Life Science, Beijing Institute of Technology, No.5,

Zhongguancun South Street, Haidian District, Beijing 100081, China

Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, the Ministry of Industry and Infor-

mation Technology, Beijing Institute of Technology, No.5, Zhongguancun South Street, Haidian District, Beijing 100081, China

Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing Institute of Technology, No.5, Zhongguan-

cun South Street, Haidian District, Beijing 100081, China

Faculty of Engineering, Kagawa University, 2217-20 Hayashi-cho, Takamatsu, Kagawa, Japan

panshaowu.hit@gmail.com, shiliwei@bit.edu.cn, guoshuxiang@bit.edu.cn

Corresponding author

Abstract – A moving target detection and tracking system is

critical important for autonomous mobile robot to accomplish

complicated tasks. Aiming at application requirements of our

amphibious spherical robot proposed in previous researches, a

low-power and portable moving target detection system was de-

signed and implemented in this paper. Xilinx Zynq-7000 SoC

(System on Chip) was used to fabricate the image processing

system of the robot for detection and tracking. An OmniVision

OV7670 COMS image sensor controlled by customized IP cores

in the PL (Programmable Logic) of the SoC was adopted to ac-

quire 640×480 RGB images at 30 frames per second. The Gaus-

sian background modeling method was implemented with Vivado

HLS in the PL to detect moving targets. And a FCT (Fast Com-

pressive Tracking) tracker with motion estimation mechanism

was running in the PS (Processing System) of the SoC to track

targets captured by the detection subsystem subsequently. Be-

sides, the dynamical power management (DPM) and the dynami-

cal voltage frequency scaling (DVFS) mechanisms were used for

a higher power-efficiency. Experimental results verified the vali-

dation and performance of the detection system. The design in

this paper may have reference value for vision-based mobile ro-

bots or vehicles.

Index Terms – Moving target detection. Gaussian background

modeling. Low-power. Zynq-7000 SoC. Amphibious spherical ro-

bot.

I. INTRODUCTION

As one of the most effective and feasible tools to sense the

surroundings [1], digital cameras have been widely used in

mobile robots to realized intelligent methods. Among various

vision systems of a mobile robot, the moving target detection

and tracking system often plays a critical important role to

realize robotic functions, such as autonomous navigation [2],

visual servoing [3], path planning [4], robot–human interac-

tion [5] and et al.

Target detection is the process to probe motions or beha-

viors of targets by analyzing the scenarios in image sequences

and then mark coordinates of the moving targets [6]. The most

common detection algorithms include the background subtrac-

tion method [7], the optical flow method [8], the template

matching method [9], etc. The background subtraction method

extracts the foreground or target by calculating the error be-

tween an image from the video and the image of background

[10]. The optical flow method detects moving targets by cal-

culating the optical flow field of images and then analyzing

the velocity vector features [11]. The template matching me-

thod, which is usually used for stationary target detection or

works as an assist module for robust target tracking, locates

specific targets by compare features such as color [12], con-

tour [13], SIFT (Scale Invariant Feature Transform) [14], etc.

In recent years, most researchers have combined studies of

target detection with machine learning theories, and tried to

improve the precision of detection with pattern classification

algorithms [15]. And some state-of-the-art detection algo-

rithms, which were built upon SVM (Support Vector Ma-

chine) [17], Adaboost [18], wavelet [19], etc., have been pro-

posed.

However, most related studies mainly aimed at improving

the precision of detection, while the computational consump-

tion and usability of algorithms were sometimes overlooked.

Unlike theoretical studies conducted on high performance

desktops or workstations, target detection and tracking for

robotic applications are usually based on embedded micropro-

cessors and limited power supply. Thus the real-time perfor-

mance of the detection algorithm and the power consumption

of the whole system have to be taken into consideration.

FPGA (Field Programmable Gate Array) [19] and DSP (Digi-

tal Signal Processor) [20] were adopted to implement real-

time portable detection and tracking systems in some studies,

but few studies pay close attention to low-power system de-

sign and global power optimization [21].

To meet requirements of our amphibious spherical robots,

which necessitated even stricter constraints on power con-

sumption and heat of circuits, a novel low-power moving tar-

get detection system was designed and implemented in this

paper. The latest Xilinx Zynq-7000 SoC (System on Chip)

was adopted to fabricate the electrical system of our robot for

control and vision applications. OmniVision OV7670, which

is a compact CMOS camera controlled by IP cores in the PL

(Programmable Logic) of the SoC, was used to capture

640×480 RGB images at the rate of 30 fps (frames per

second). The Gaussian background modeling method was im-

plemented with Vivado HLS in the PL of the SoC to detect

1116

Proceedings of 2015 IEEE

International Conference on Mechatronics and Automation

August 2 - 5, Beijing, China

本内容试读结束，登录后可阅读更多

下载后可阅读完整内容，剩余5页未读，立即下载

评论收藏

内容反馈

weixin_38543293

粉丝: 7
资源: 963

基于低功耗SoC的两栖球形机器人运动目标检测系统

两栖球形机器人控制系统研究.pdf

基于STM32的陆空两栖机器人控制系统开发.zip

球形机器人_球形机器人_

基于STM32的六足机器人运动控制系统研究.pdf

基于3861的智慧灯光球形机器人

基于开源倍福控制系统的机器人控制系统设计.pdf

基于STM32的陆空两栖机器人控制系统开发.pdf

_基于三轴重力加速度传感器的机器人状态检测.docx

基于FPGA的机器人运动控制系统

基于FPGA的运动目标检测相关的几篇学位论文

超低功耗单片无线系统应用入门：基于2.4GHz无线SoC芯片nRF24LE1

基于嵌入式Linux的运动目标检测系统.pdf

基于嵌入式的机器人目标识别视觉系统设计 20181126

基于STM32的下肢康复机器人控制系统设计.pdf

NXP低功耗蓝牙控制的机器人参考设计.pdf

基于STM32的智能扫地机器人避障系统设计的研究_万军

工业机器人运动控制系统设计研究.pdf

基于ARM的自动施肥农业机器人系统研究.pdf

基于springboot的智能管道检测机器人软件设计-iData

超低功耗单片无线系统应用入门源程序

解决 SoC 低功耗验证的挑战

多尺度特征融合的煤矿救援机器人目标检测模型.pdf

基于强跟踪滤波的机器人运动轨迹控制系统设计.pdf

基于运动控制卡的桁架机器人控制系统设计.pdf

基于STM32的三轮全向机器人运动控制系统设计.zip

基于STM32自动网球拾取机器人设计.pdf

基于STM32的机器人运动精确控制系统设计.pdf

最新资源